Search

Ultrasound stimulated microbubbles (USMB) are being investigated for their potential to promote the uptake of anticancer agents into tumor tissue by exploiting their ability to enhance microvascular permeability. At sufficiently high ultrasound transmit amplitudes it has also recently been shown that USMB treatments can, on their own, induce vascular damage, shutdown blood flow, and inhibit tumor growth. The objective of this study is to examine the antitumor effects of ‘antivascular’ USMB treatments in conjunction with chemotherapy, which differs from previous work which has sought to enhance drug uptake with USMBs by increasing vascular permeability. Conceptually this is a strategy similar to combining vascular disrupting agents with a chemotherapy, and we have selected the taxane docetaxel (Taxotere) for evaluating this approach as it has previously been shown to have potent antitumor effects when combined with small molecule vascular disrupting agents. Experiments were conducted on PC3 tumors implanted in athymic mice. USMB treatments were performed at a frequency of 1 MHz employing sequences of 50 ms bursts (0.00024 duty cycle) at 1.65 MPa. USMB treatments were administered on a weekly basis for 4 weeks with docetaxel (DTX) being given intravenously at a dose level of 5 mg/kg. The USMB treatments, either alone or in combination with DTX, induced an acute reduction in tumor perfusion which was accompanied at the 24 hour point by significantly enhanced necrosis and apoptosis. Longitudinal experiments showed a modest prolongation in survival but no significant growth inhibition occurred in DTX–only and USMB-only treatment groups relative to control tumors. The combined USMB-DTX treatment group produced tumor shrinkage in weeks 4–6, and significant growth inhibition and survival prolongation relative to the control (p

Dipender Gill and Stephen Burgess discuss the accompanying study by James Yarmolinsky and colleagues investigating the associations between genetically-proxied inhibition of antihypertensive drug targets and risk of common cancer subtypes using Mendelian randomization.

Purpose Percutaneous hepatic perfusion with melphalan (M-PHP) is increasingly used in patients with liver metastases from various primary tumors, yet data on colorectal liver metastases (CRLM) are limited. The aim of this study was to prospectively evaluate the efficacy and safety of M-PHP in patients with CRLM. Materials and methods Prospective, single-center, single-arm phase II study of M-PHP with hemofiltration in patients with unresectable CRLM. Proven, extrahepatic metastatic disease was one of the exclusion criteria. Primary outcomes were overall response rate (ORR) and best overall response (BOR). Secondary outcomes were overall survival (OS), progression-free survival (PFS), hepatic PFS (hPFS), and safety. Results A total of 14 M-PHP procedures were performed in eight patients between March 2014 and December 2015. All patients (median age 56 years, ranging from 46 to 68) had received (extensive) systemic chemotherapy before entering the study. The ORR was 25.0%, with two out of eight patients showing partial response as BOR. Median OS was 17.3 months (ranging from 2.6 to 30.9) with a one-year OS of 50.0%. Median PFS and hPFS were 4.4 and 4.5 months, respectively. No serious adverse events occurred. Grade 3/4 hematologic adverse events were observed in the majority of patients, though all were transient and well-manageable. Conclusion M-PHP is a safe procedure with only limited efficacy in patients with unresectable CRLM who already showed progression of disease after receiving one or more systemic treatment regimens.

Funder: NIHR Cambridge Biomedical Research Centre, Funder: Addenbrooke’s Charitable Trust, Funder: National Institute for Health Research (NIHR), Funder: Mark Foundation For Cancer Research, Funder: Cambridge Commonwealth, European and International Trust, Funder: Cancer Research UK, Funder: Cambridge Clinical Trials Unit, Funder: Cancer Research UK Cambridge Centre, Funder: Engineering and Physical Sciences Research Council Cancer Imaging Centre in Cambridge and Manchester, Funder: Cambridge Experimental Cancer Medicine Centre, PURPOSE: To detect early response to sunitinib treatment in metastatic clear cell renal cancer (mRCC) using multiparametric MRI. METHOD: Participants with mRCC undergoing pre-surgical sunitinib therapy in the prospective NeoSun clinical trial (EudraCtNo: 2005-004502-82) were imaged before starting treatment, and after 12 days of sunitinib therapy using morphological MRI sequences, advanced diffusion-weighted imaging, measurements of R2* (related to hypoxia) and dynamic contrast-enhanced imaging. Following nephrectomy, participants continued treatment and were followed-up with contrast-enhanced CT. Changes in imaging parameters before and after sunitinib were assessed with the non-parametric Wilcoxon signed-rank test and the log-rank test was used to assess effects on survival. RESULTS: 12 participants fulfilled the inclusion criteria. After 12 days, the solid and necrotic tumor volumes decreased by 28% and 17%, respectively (p = 0.04). However, tumor-volume reduction did not correlate with progression-free or overall survival (PFS/OS). Sunitinib therapy resulted in a reduction in median solid tumor diffusivity D from 1298x10-6 to 1200x10-6mm2/s (p = 0.03); a larger decrease was associated with a better RECIST response (p = 0.02) and longer PFS (p = 0.03) on the log-rank test. An increase in R2* from 19 to 28s-1 (p = 0.001) was observed, paralleled by a decrease in Ktrans from 0.415 to 0.305min-1 (p = 0.01) and a decrease in perfusion fraction from 0.34 to 0.19 (p

Background and aims The aim of this study was to investigate the relationship between body composition before lenvatinib treatment and prognosis in patients with hepatocellular carcinoma (HCC). We also assessed the relationship between the rate of change in body composition after lenvatinib treatment and prognosis. Methods Eighty-one patients with advanced HCC who were treated with lenvatinib were enrolled. We assessed prognosis, various clinical data, body composition parameters obtained by bioelectrical impedance analysis (BIA), and handgrip strength. Results Multivariate analysis showed that an extracellular water to total body water ratio (ECW/TBW) ≤ 0.400 at treatment initiation was associated with longer overall survival (OS), progression-free survival (PFS), and post-progression survival (PPS) (OS: hazard ratio [H0R], 4.72; 95% CI, 12.03–11.00; P < 0.001; PFS: HR, 2.66; 95% CI, 1.33–5.34; P = 0.0057; PPS: HR, 3.08; 95% CI, 1.32–7.18; P = 0.0093). Multivariate analysis also showed that the skeletal muscle mass index (SMI) of the arm at treatment initiation was associated with a longer PFS (HR, 2.12; 95% CI, 1.23–3.64; P = 0.0069). In the group with an ECW/TBW ≤ 0.400 before lenvatinib treatment, univariate analysis showed that the rate of change in only the arm SMI was associated with a longer OS and PFS. Conclusion Body composition assessment by BIA before and after lenvatinib treatment is useful in predicting prognosis in lenvatinib-treated patients with HCC.

Background Mucosal infiltration by certain bacterial species may contribute to the development and progression of colorectal cancer (CRC). There is considerable variation in reported detection rates in human CRC samples and the extent to which bacterial infiltration varies across regions of the primary tumour is unknown. This study aimed to determine if there is an optimal site for bacterial detection within CRC tumours. Methods Presence of target bacterial species was assessed by quantitative real-time PCR (qPCR) in 42 human CRC tumours. Abundance in primary tumour regions, normal epithelium and at metastatic sites was investigated in an expanded cohort of 51 patients. Species presence/absence was confirmed by diversity profiling in five patients. Correlation with total bacterial load and clinicopathological features was assessed. Results Fusobacterium nucleatum and Bacteroides fragilis were detected in tumours from 43% and 24% of patients, respectively (17% positive for both species). The optimal detection site was the tumour luminal surface (TLS). Patients testing positive at the TLS frequently tested negative at other sites, including central tumour and invasive margin. F. nucleatum was detected at a higher frequency in tumour versus normal epithelium (p < 0.01) and was associated with more advanced disease (p = 0.01). Detection of both species correlated with total bacterial load. However, corroboration of qPCR results via diversity profiling suggests detection of these species may indicate a specific microbial signature. Conclusions This study supports a role for F. nucleatum in CRC development. Presence of F. nucleatum and B. fragilis varies across primary tumour regions, with the TLS representing the optimal site for bacterial detection.

Nivolumab, an immune checkpoint blocker, has been approved for advanced gastric cancer (GC), but predictive factors of nivolumab’s efficacy in patients with GC, especially immune cells such as tissue-resident memory T cells or those forming tertiary lymphoid structures (TLS), remain unclear. Tissue samples were obtained from surgically resected specimens of patients with GC who were treated with nivolumab as third-line or later treatment. Immunohistochemical staining was performed to detect the presence of TLS and CD103+T cells and assess the association between TLSs and response to nivolumab treatment. A total of 19 patients were analyzed. In patients with partial response (PR) to nivolumab, numerous TLS were observed, and CD103+T cells were found in and around TLS. Patients with many TLS experienced immune-related adverse events more often than those with few TLS (p= 0.018). The prognosis of patients with TLS high was better than those with TLS low. Patients with a combination of TLS high and CD103 high tended to have a better prognosis than other groups. Our results suggested that TLS status might be a predictor of nivolumab effectiveness.

Endometrioid endometrial carcinomas (EECs) are the most common histological subtype of uterine cancer. Late-stage disease is an adverse prognosticator for EEC. The purpose of this study was to analyze EEC exome mutation data to identify late-stage-specific statistically significantly mutated genes (SMGs), which represent candidate driver genes potentially associated with disease progression. We exome sequenced 15 late-stage (stage III or IV) non-ultramutated EECs and paired non-tumor DNAs; somatic variants were called using Strelka, Shimmer, SomaticSniper and MuTect. Additionally, somatic mutation calls were extracted from The Cancer Genome Atlas (TCGA) data for 66 late-stage and 270 early-stage (stage I or II) non-ultramutated EECs. MutSigCV (v1.4) was used to annotate SMGs in the two late-stage cohorts and to derive p-values for all mutated genes in the early-stage cohort. To test whether late-stage SMGs are statistically significantly mutated in early-stage tumors, q-values for late-stage SMGs were re-calculated from the MutSigCV (v1.4) early-stage p-values, adjusting for the number of late-stage SMGs tested. We identified 14 SMGs in the combined late-stage EEC cohorts. When the 14 late-stage SMGs were examined in the TCGA early-stage data, only Krüppel-like factor 3 (KLF3) and Paired box 6 (PAX6) failed to reach significance as early-stage SMGs, despite the inclusion of enough early-stage cases to ensure adequate statistical power. Within TCGA, nonsynonymous mutations in KLF3 and PAX6 were, respectively, exclusive or nearly exclusive to the microsatellite instability (MSI)-hypermutated molecular subgroup and were dominated by insertions-deletions at homopolymer tracts. In conclusion, our findings are hypothesis-generating and suggest that KLF3 and PAX6, which encode transcription factors, are MSI target genes and late-stage-specific SMGs in EEC.

Purpose Hepatocellular carcinoma (HCC) patients usually achieve a complete response after treatment. This study was aimed to assess the clinical outcome of HCC patients who had achieved a complete response but later presented with elevated tumor marker levels without an identifiable recurrent tumor on gadoxetic acid-enhanced magnetic resonance imaging (MRI). Methods We retrospectively reviewed the clinical outcome of 58 HCC treated patients who had achieved a complete response but later was referred to our institution’s multidisciplinary tumor board for a clinically suspected hidden HCC recurrence based on elevated tumor marker levels but negative gadoxetic acid-enhanced MRI. The imaging studies, tumor markers, and clinical information were reviewed. The total follow-up period was at least 15 months after the initial negative gadoxetic acid-enhanced MRI. Results Follow-up imaging studies detected an HCC lesion in 89.7% (n = 52/58) of the patients within the study period, and approximately half of the tumors (46.2%, n = 24/52) developed within 3 months. The most frequent site of recurrence was the liver (86.5%; n = 45/52), but extra-hepatic metastasis was also common (19.2%; n = 10/52). In 5.8% (n = 3/52), HCC reoccurred in the combined form of intra-hepatic and extra-hepatic recurrence. Extra-hepatic metastasis alone occurred in 13.5% (n = 7/52) of patients. Conclusions HCC frequently recurred within a short interval in patients who achieved a complete response to treatment in the presence of increased tumor marker levels, even if gadoxetic acid-enhanced MRI was negative. Under such circumstances, we suggest a short-term follow-up including, but not limited to, gadoxetic acid-enhanced MRI along with systemic evaluation.

Objective This study is to explore the correlation between the contrast-enhanced ultrasound (CEUS) characteristics of breast cancer and the epithelial-mesenchyme transformation (EMT). Methods Totally 119 patients of breast cancer underwent CEUS. Tissues in the active area were collected and subjected to the immunohistochemical detection, PT-PCR and Western blot. Correlation analysis was conducted between the clinical pathological parameters and the CEUS indicators. Results The expression levels of CD44, N-cadherin, and β-catenin in breast cancer tissues were higher than those in adjacent tissues (PE-cadherin mRNA and Vimentin levels between cancer and adjacent tissues (P>0.05). The expressions were up-regulated in the CSCs, with higher histological grade, lymph node metastasis, and negative estrogen receptor (ER) expression. Smaller breast tumors, with no lymph node metastasis, lower clinical stage, and positive ER expression, tended to exhibit the up-regulated epithelial phenotype. Breast tumors, with high histological grade, lymph node metastasis, high clinical staging grade, and negative ER expression, tended to exhibit the up-regulated interstitial phenotype. The peak intensity of the time-intensity curve (TIC) for the CEUS was positively correlated with the CSC marker CD44 and the interstitial phenotype marker N-cadherin. The starting time of enhancement was negatively correlated with the N-cadherin. Area under the curve was positively correlated with the expression of CD44 and N-cadherin, while negatively correlated with the epithelial phenotype marker β-catenin. The time to peak was negatively correlated with the interstitial phenotypes Vimentin and N-cadherin, with no correlation with the E-cadherin or β-catenin. Conclusion Breast cancers show the enlarged lesions after enlargement and perfusion defect for the CEUS. The fast-in pattern, high enhancement, and high perfusion in the TIC are correlated with the CSCs and EMT expressions, suggesting poor disease prognosis.

The design of efficient combination therapies is a difficult key challenge in the treatment of complex diseases such as cancers. The large heterogeneity of cancers and the large number of available drugs renders exhaustive in vivo or even in vitro investigation of possible treatments impractical. In recent years, sophisticated mechanistic, ordinary differential equation-based pathways models that can predict treatment responses at a molecular level have been developed. However, surprisingly little effort has been put into leveraging these models to find novel therapies. In this paper we use for the first time, to our knowledge, a large-scale state-of-the-art pan-cancer signaling pathway model to identify candidates for novel combination therapies to treat individual cancer cell lines from various tissues (e.g., minimizing proliferation while keeping dosage low to avoid adverse side effects) and populations of heterogeneous cancer cell lines (e.g., minimizing the maximum or average proliferation across the cell lines while keeping dosage low). We also show how our method can be used to optimize the drug combinations used in sequential treatment plans—that is, optimized sequences of potentially different drug combinations—providing additional benefits. In order to solve the treatment optimization problems, we combine the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm with a significantly more scalable sampling scheme for truncated Gaussian distributions, based on a Hamiltonian Monte-Carlo method. These optimization techniques are independent of the signaling pathway model, and can thus be adapted to find treatment candidates for other complex diseases than cancers as well, as long as a suitable predictive model is available., Author summary Combination therapies are a promising approach to counter complex diseases such as cancers. Two key difficulties in the design of effective cancer combination therapies are the large number of available drugs and the heterogeneity of cancers which render exhaustive laboratory studies impractical. In recent years, sophisticated signaling pathway models that can predict responses to combination treatments at a molecular level have been developed. This motivates the question of how one can leverage mechanistic models to identify candidates for novel combination treatments. In this paper we propose a combination treatment optimization framework which employs a large-scale pan-cancer pathway model. We formulate treatment optimization problems for single cell lines and heterogeneous populations of cancer cells. We further investigate sequential treatment plans and combine an existing evolutionary algorithm with an efficient Hamiltonian Monte-Carlo based sampling scheme. During extensive simulation studies our approach identified combination therapies which are predicted to be more effective than conventional treatments. We hope that one day in silico experiments will be used to identify a small set of promising treatment candidates which can then form a starting point for laboratory studies, allowing for an efficient use of limited resources and accelerated discovery of effective therapies.

Cancer reflects the dysregulation of the underlying gene network, which is strongly related to the 3D genome organization. Numerous efforts have been spent on experimental characterizations of the structural alterations in cancer genomes. However, there is still a lack of genomic structural-level understanding of the temporal dynamics for cancer initiation and progression. Here, we use a landscape-switching model to investigate the chromosome structural transition during the cancerization and reversion processes. We find that the chromosome undergoes a non-monotonic structural shape-changing pathway with initial expansion followed by compaction during both of these processes. Furthermore, our analysis reveals that the chromosome with a more expanding structure than those at both the normal and cancer cell during cancerization exhibits a sparse contact pattern, which shows significant structural similarity to the one at the embryonic stem cell in many aspects, including the trend of contact probability declining with the genomic distance, the global structural shape geometry and the spatial distribution of loci on the chromosome. In light of the intimate structure-function relationship at the chromosomal level, we further describe the cell state transition processes by the chromosome structural changes, suggesting an elevated cell stemness during the formation of the cancer cells. We show that cell cancerization and reversion are highly irreversible processes in terms of the chromosome structural transition pathways, spatial repositioning of chromosomal loci and hysteresis loop of contact evolution analysis. Our model draws a molecular-scale picture of cell cancerization from the chromosome structural perspective. The process contains initial reprogramming towards the stem cell followed by the differentiation towards the cancer cell, accompanied by an initial increase and subsequent decrease of the cell stemness., Author summary Cancer is among the leading causes of human death. Cancer is regulated by the underlying regulatory network of gene expressions, which are in intimate relation to the 3D chromosome architectures. Numerous efforts have been spent on elucidating the chromosome structural variants in tumorigenesis, while the dynamical picture of how chromosomes structurally evolve during cancer formation is still missing. Here we integrate the Hi-C data into the polymer simulations to build the chromosome structural ensembles in the normal and cancer cells. Then we use a nonequilibrium landscape-switching model to simulate the chromosome structural dynamics during the cancerization and reversion processes. With quantified pathways, we show that the chromosomes at transient intermediate states in the cancer formation possess a significant degree of structural similarity to those at the stem cell. Our findings indicate the formation of stem-like states during cancer formation from the chromosome structural perspective. We draw a molecular-scale picture of the cancer formation, which contains initial reprogramming towards the stem cell followed by differentiation towards the cancer cell.

Cholangiocarcinoma (CCA) is a group of heterogenous malignancies arising from bile duct epithelium with distinct pathological features. Adaptor proteins have implicated in cell proliferation, migration, and invasion of different cancer cells. The objective of this study was to assess whether the adaptor protein XB130 (AFAP1L2) is a critical biological determinant of CCA outcome. XB130 expression levels were investigated in four CCA cell lines compared to an immortalized cholangiocyte cell line by Western blotting. Small interfering (si) RNA-mediated XB130 gene silencing was conducted to evaluate the effects of reduced XB130 expression on cell proliferation, migration, and invasion by MTT, transwell migration and cell invasion assay. The immunohistochemical quantification of XB130 levels were performed in surgically resected formalin-fixed, paraffin-embedded specimens obtained from 151 CCA patients. The relationship between XB130 expression and the clinicopathological parameters of CCA patients were analyzed. Our results showed that XB130 was highly expressed in KKU-213A cell line. Knockdown of XB130 using siRNA significantly decreased the proliferation, migration, and invasion properties of KKU-213A cells through the inhibition of PI3K/Akt pathway, suggesting that XB130 plays an important role in CCA progression. Moreover, elevated XB130 expression levels were positive relationship with lymphovascular space invasion (LVSI), intrahepatic type of CCA, high TNM staging (stage III, IV), high T classification (T3, T4), and lymph node metastasis. We provide the first evidence that the overexpression of XB130 is associated with tumorigenic properties of CCA cells, leading to CCA progression with aggressive clinical outcomes.

Background:There was no clear evidence whether the initial dose of enzalutamide affects the incidence of adverse events (AEs), and oncological outcome in patients with castration-resistant prostate cancer (CRPC).\nMethods:The clinical charts of 233 patients with CRPC treated with enzalutamide were reviewed retrospectively. After 1:3 propensity score matching (PSM), 124 patients were divided into a reduced dose group and a standard dose group, and the prostate specific antigen (PSA) response and the incidence of AEs were compared.\nResults:190 patients with CRPC initiated with standard dose enzalutamide were younger and better performance status compared with 43 patients beginning with reduced dose. After PSM, the baseline characteristics were not different between the standard and the reduced dose group. In the PSM cohort, the PSA response rate was significantly lower in the reduced dose group than in the standard dose group (-66.3% and -87.4%, p = 0.02). The incidence rates of AEs were not statistically different between the groups (22.6% and 34.4%, respectively, p = 0.24).\nConclusion:\nInitiating treatment with a reduced dose of enzalutamide did not significantly decrease the incidence rate of AEs, and it showed poorer PSA response rate. There is no clear rationale for treating with a reduced initial dose of enzalutamide to reduce the incidence of AEs., 論文

With the advance of precision medicine, the availability of tumor tissue for molecular analysis has become a limiting factor. This is particularly the case for bone metastases which are frequently occurring in cancer types such as prostate cancer. Due to the necessary decalcification process it was long thought that transcriptome analysis will not be feasible from decalcified formalin-fixed, paraffin-embedded (DFFPE) in a large manner. Here we demonstrate that mRNA extraction from DFFPE is feasible, quick, robust and reproducible and that decalcification does not hamper subsequent gene expression analysis. This might assist in implementing transcriptome analysis from DFFPE into every day practice.

Background Although low skeletal muscle mass has an adverse impact on the treatment outcomes of cancer patients, whether the relationship between preoperative skeletal muscle mass and gastrectomy outcomes in gastric cancer (GC) differs between men and women is unclear. The study aimed to clarify this relationship based on gender. Methods Between January 2007 and December 2015, 1054 patients who underwent gastrectomy for GC at Osaka City General Hospital were enrolled in this study. We evaluated sarcopenia by the skeletal muscle index (SMI), which was measured by computed tomography (CT) using areas of muscle in the third lumbar vertebral body (L3). Male and female patients were each divided into two groups (low skeletal muscle and high skeletal muscle). Results The SMI emerged as an independent predictor of 5-year overall survival (OS) in male GC patients (Hazard ratio 2.51; 95% confidence interval (CI) 1.73–3.63, p < 0.001) based on multivariate analysis. However, this index was not an independent predictive determinant of 5-year cancer-specific survival (CSS). The SMI was not an independent predictor of either OS or CSS in female GC patients. The incidence of leakage and major complication (Clavien Dindo grade ≧ 3) did not differ significantly across groups. Conclusions Preoperative skeletal muscle mass is a valuable prognostic predictor of OS in male GC patients.

In searching for novel targeted therapeutic agents for lung cancer treatment, norcycloartocarpin from Artocarpus gomezianus was reported in this study to promisingly interacted with Akt and exerted the apoptosis induction and epithelial-to-mesenchymal transition suppression. Selective cytotoxic profile of norcycloartocarpin was evidenced with approximately 2-fold higher IC50 in normal dermal papilla cells (DPCs) compared with human lung cancer A549, H460, H23, and H292 cells. We found that norcycloartocarpin suppressed anchorage-independent growth, cell migration, invasion, filopodia formation, and decreased EMT in a dose-dependent manner at 24 h, which were correlated with reduced protein levels of N-cadherin, Vimentin, Slug, p-FAK, p-Akt, as well as Cdc42. In addition, norcycloartocarpin activated apoptosis caspase cascade associating with restoration of p53, down-regulated Bcl-2 and augmented Bax in A549 and H460 cells. Interestingly, norcycloartocarpin showed potential inhibitory role on protein kinase B (Akt) the up-stream dominant molecule controlling EMT and apoptosis. Computational molecular docking analysis further confirmed that norcycloartocarpin has the best binding affinity of -12.52 kcal/mol with Akt protein at its critical active site. As Akt has recently recognized as an attractive molecular target for therapeutic approaches, these findings support its use as a plant-derived anticancer agent in cancer therapy.

Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a ‘low-quality’ cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA (mtDNA) encoded genes and (ii) if a small number of genes are detected. Current best practices use these QC metrics independently with either arbitrary, uniform thresholds (e.g. 5%) or biological context-dependent (e.g. species) thresholds, and fail to jointly model these metrics in a data-driven manner. Current practices are often overly stringent and especially untenable on certain types of tissues, such as archived tumor tissues, or tissues associated with mitochondrial function, such as kidney tissue [1]. We propose a data-driven QC metric (miQC) that jointly models both the proportion of reads mapping to mtDNA genes and the number of detected genes with mixture models in a probabilistic framework to predict the low-quality cells in a given dataset. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses. Our software package is available at https://bioconductor.org/packages/miQC., Author summary We developed the miQC package to predict the low-quality cells in a given scRNA-seq dataset by jointly modeling both the proportion of reads mapping to mitochondrial DNA (mtDNA) genes and the number of detected genes using mixture models in a probabilistic framework. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses.

The C-X-C chemokine receptor 4 (CXCR4) is G protein-coupled receptor that upon binding to its cognate ligand, can lead to tumor progression. Several CXCR4-targeted therapies are currently under investigation, and with it comes the need for imaging agents capable of accurate depiction of CXCR4 for therapeutic stratification and monitoring. PET agents enjoy the most success, but more cost-effective and radiation-free approaches such as ultrasound (US) imaging could represent an attractive alternative. In this work, we developed a targeted microbubble (MB) for imaging of vascular CXCR4 expression in cancer. A CXCR4-targeted MB was developed through incorporation of the T140 peptide into the MB shell. Binding properties of the T140-MB and control, non-targeted MB (NT-MB) were evaluated in MDA-MB-231 cells where CXCR4 expression was knocked-down (via shRNA) through optical imaging, and in the lymphoma tumor models U2932 and SuDHL8 (high and low CXCR4 expression, respectively) by US imaging. PET imaging of [18F]MCFB, a tumor-penetrating CXCR4-targeted small molecule, was used to provide whole-tumor CXCR4 readouts. CXCR4 expression and microvessel density were performed by immunohistochemistry analysis and western blot. T140-MB were formed with similar properties to NT-MB and accumulated sensitively and specifically in cells according to their CXCR4 expression. In NOD SCID mice, T140-MB persisted longer in tumors than NT-MB, indicative of target interaction, but showed no difference between U2932 and SuDHL8. In contrast, PET imaging with [18F]MCFB showed a marked difference in tumor uptake at 40–60 min post-injection between the two tumor models (pEx vivo analysis revealed that the large differences in CXCR4 expression between the two models are not reflected in the vascular compartment, where the MB are restricted; in fact, microvessel density and CXCR4 expression in the vasculature was comparable between U2932 and SuDHL8 tumors. In conclusion, we successfully developed a T140-MB that can be used for imaging CXCR4 expression in the tumor vasculature.

The treatment response to anti-angiogenic agents varies among cancer patients and predictive biomarkers are needed to identify patients with resistant cancer or guide the choice of anti-angiogenic treatment. We present “the Cancer Angiogenesis Co-Culture (CACC) assay”, an in vitro Functional Precision Medicine assay which enables the study of tumouroid induced angiogenesis. This assay can quantify the ability of a patient-derived tumouroid to induce vascularization by measuring the induction of tube formation in a co-culture of vascular cells and tumoroids established from the primary colorectal tumour or a metastasis. Furthermore, the assay can quantify the sensitivity of patient-derived tumoroids to anti-angiogenic therapies. We observed that tube formation increased in a dose-dependent manner upon treatment with the pro-angiogenic factor vascular endothelial growth factor A (VEGF-A). When investigating the angiogenic potential of tumoroids from 12 patients we found that 9 tumoroid cultures induced a significant increase in tube formation compared to controls without tumoroids. In these 9 angiogenic tumoroid cultures the tube formation could be abolished by treatment with one or more of the investigated anti-angiogenic agents. The 3 non-angiogenic tumoroid cultures secreted VEGF-A but we observed no correlation between the amount of tube formation and tumoroid-secreted VEGF-A. Our data suggests that the CACC assay recapitulates the complexity of tumour angiogenesis, and when clinically verified, could prove a valuable tool to quantify sensitivity towards different anti-angiogenic agents.

Epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition (MET), are believed to play key roles in facilitating the metastatic cascade. Metastatic lesions often exhibit a similar epithelial-like state to that of the primary tumour, in particular, by forming carcinoma cell clusters via E-cadherin-mediated junctional complexes. However, the factors enabling mesenchymal-like micrometastatic cells to resume growth and reacquire an epithelial phenotype in the target organ microenvironment remain elusive. In this study, we developed a workflow using image-based cell profiling and machine learning to examine morphological, contextual and molecular states of individual breast carcinoma cells (MDA-MB-231). MDA-MB-231 heterogeneous response to the host organ microenvironment was modelled by substrates with controllable stiffness varying from 0.2kPa (soft tissues) to 64kPa (bone tissues). We identified 3 distinct morphological cell types (morphs) varying from compact round-shaped to flattened irregular-shaped cells with lamellipodia, predominantly populating 2-kPa and >16kPa substrates, respectively. These observations were accompanied by significant changes in E-cadherin and vimentin expression. Furthermore, we demonstrate that the bone-mimicking substrate (64kPa) induced multicellular cluster formation accompanied by E-cadherin cell surface localisation. MDA-MB-231 cells responded to different substrate stiffness by morphological adaptation, changes in proliferation rate and cytoskeleton markers, and cluster formation on bone-mimicking substrate. Our results suggest that the stiffest microenvironment can induce MET., Author summary The epithelial-mesenchymal transition (EMT), a process by which epithelial cells lose their cell polarity and cell-cell adhesion and gain migratory and invasive properties to become mesenchymal cells, is believed to play the key role in the initiation of the metastatic cascade. The ability of mesenchymal cells to survive, transform and establish colonies in distant organs is well known but not well understood. To gain insight into this process, we developed a workflow using machine learning and image analysis of cells to examine how morphology (or physical form and structure) and biochemical properties of individual (triple negative) breast carcinoma cells vary in response to their interaction with a substrate of variable stiffness. We found that mesenchymal breast cancer cells responded to different substrate stiffness by morphological adaptation, changes in proliferation rate and cytoskeleton markers such as cell-cell adhesion protein E-cadherin. Surprisingly, the cell properties on the stiffest tested substrate that mimicked bone stiffness changed dramatically–they formed multicellular clusters with distinct E-cadherin localisation at the cell-cell adhesion surfaces. Our results suggest that the stiffest microenvironment can induce cell transitioning from mesenchymal to epithelial cell phenotype.

Background/Objectives Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy associated with high metastatic risk. Prognosis remains poor even after resection. Previously our group identified biomarkers that improved diagnostic accuracy in PDAC beyond the established diagnostic tumour marker, CA19-9. Risk factors, symptoms and circulating biomarkers associated with a PDAC diagnosis may differ from those that alter disease progression and metastasis. This study aimed at assessing the risk factors, presenting symptoms and potential prognostic biomarkers in PDAC and determine their relationship with PDAC stage and/or metastatic status. Methods Seventy-two PDAC patients with imaging available for TNM staging at presentation were enrolled following informed consent. Demographic and clinical data were captured. Blood was collected and 38 cytokines/angiogenic factors measured. Nonparametric association tests, univariate and multivariate logistic regression were performed using STATA version 14.2. A p-value≤0.05 was considered significant and odds ratios reported for effect size. Results Most risk factors and symptoms did not differ across the stages of cancer. Although male gender and smoking are risk factors for PDAC, the majority of study patients with metastatic PDAC were non-smoking females. In addition to CA19-9, the platelet count (p Conclusions Platelet count, IL-15 and GM-CSF are potential prognostic indicators of metastatic disease in PDAC patients from our local South African population.

PLOS ONE 16(8), 0255983 (2021). doi:10.1371/journal.pone.0255983, Published by PLOS, San Francisco, California, US

Cancer is the result of mutagenic processes that can be inferred from tumor genomes by analyzing rate spectra of point mutations, or “mutational signatures”. Here we present SparseSignatures, a novel framework to extract signatures from somatic point mutation data. Our approach incorporates a user-specified background signature, employs regularization to reduce noise in non-background signatures, uses cross-validation to identify the number of signatures, and is scalable to large datasets. We show that SparseSignatures outperforms current state-of-the-art methods on simulated data using a variety of standard metrics. We then apply SparseSignatures to whole genome sequences of pancreatic and breast tumors, discovering well-differentiated signatures that are linked to known mutagenic mechanisms and are strongly associated with patient clinical features., Author summary Cancer is a genetic disease, occurring as a result of mutagenic processes causing DNA somatic mutations in genes controlling cellular growth and division. These somatic mutations arise from processes such as defective DNA repair and environmental mutagens, which massively increase the rate of somatic variants. As a result, due to the specificity of molecular lesions caused by such processes, and the specific repair mechanisms deployed by the cell to mitigate the damage, mutagenic processes generate characteristic point mutation rate spectra which are called mutational signatures. These signatures can indicate which mutagenic processes are active in a tumor, reveal biological differences between cancer subtypes, and may be useful markers for therapeutic response. Here, we develop SparseSignatures, a novel framework for mutational signature discovery capable of both identifying the active signatures in a dataset of point mutations and calculating their exposure values, i.e., the number of mutations originating from each signature in each patient. We show that our approach outperforms current state-of-the-art methods on simulated data using a variety of standard metrics and then apply SparseSignatures to whole genome sequences of pancreatic and breast tumors, discovering well-differentiated signatures that are linked to known mutagenic mechanisms.

Introduction Radium-223, abiraterone, and enzalutamide have each been shown to significantly improve survival as monotherapy in patients with metastatic castration-resistant prostate cancer. However, effects of combination radium-223 plus abiraterone or enzalutamide on survival and safety remain unclear. Patients and methods This single-center retrospective cohort study used electronic health record data of patients with metastatic castration-resistant prostate cancer and bone metastases who were treated with radium-223 between April 1, 2014 and February 19, 2019. Patients who received radium-223 monotherapy were compared to patients who received a combination of radium-223 plus either abiraterone or enzalutamide. The primary endpoint was overall survival. Secondary endpoints included progression-free survival, time to symptomatic skeletal event, symptomatic skeletal event-free survival, and incidence of drug-related adverse events. Time-to-event analyses were estimated by log rank tests using Kaplan-Meier curves. Hazard ratios and 95% confidence intervals were derived from Cox proportional hazards models. Chi-square tests evaluated difference in serious adverse events between the two arms. Results A total of 60 patients met inclusion criteria (n = 41 in the monotherapy arm, n = 19 in the combination arm). Differences in median overall survival were not observed (12.7 vs. 12.8 months; HR 1.15, 95% CI 0.59–2.23; P = 0.68), but median progression-free survival was significantly longer in the combination arm (7.6 vs. 4.9 months; HR 1.94, 95% CI 1.11–3.40; P = 0.02). Significant differences were not observed in time to first SSE (P = 0.97), SSE-free survival (P = 0.16), or in the overall incidence of serious adverse events (P = 0.45). Conclusion Combination radium-223 plus abiraterone or enzalutamide did not improve overall survival, but prolonged progression-free survival without increasing the incidence of serious adverse events in metastatic castration-resistant prostate cancer patients with bone metastases. However, these results are limited by small numbers and patient selection inherent in retrospective analysis.

Introduction There are no reliable blood biomarkers for monitoring endometrial cancer patients in the current clinical practice. Circulating tumor DNA (ctDNA) is emerging as a promising non-invasive method to measure tumor burden, define prognosis and monitor disease status in many solid cancers. In this pilot study, we investigated if unique tumor-specific DNA junctions can be used to detect ctDNA levels in patients with endometrial cancer. Methods Chromosomal rearrangements in primary tumors of eleven patients with high-grade or advanced stage endometrial cancer were determined by whole-genome Mate-Pair sequencing. Identified unique tumor-specific junctions were evaluated in pre- and six-week post-surgery patient plasma using individualized quantitative polymerase chain reaction (qPCR) assays. The relationship between clinicopathological features and detection of ctDNA was investigated. Results CtDNA was detected in 60% (6/10) of cases pre-surgery and in 27% (3/11) post-surgery. The detection of ctDNA pre-surgery was consistent with clinical indicators of aggressive disease such as advanced stage (80% - 4/5), lymphatic spread of disease (100% - 3/3), serous histology (80% - 4/5), deep myometrial invasion (100% - 3/3), lympho-vascular space invasion (75% - 3/4). All patients in which ctDNA was detected post-surgically had type II endometrial cancer. Discussion This pilot study demonstrates the feasibility of using personalized tumor-specific junction panels for detecting ctDNA in the plasma of endometrial cancer patients. Larger studies and longer follow-up are needed to validate the potential association between pre-surgical ctDNA detection and the presence of cancers with aggressive pathologic tumor characteristics or advanced stage observed in this study.

Purposes To evaluate retropharyngeal lymph node metastasis on N stage of nasopharyngeal carcinoma (NPC). Methods NPC patients were extracted from the Surveillance, Epidemiology, and End Results database between 2004 and 2016. Pathologically confirmed patients with complete data of retropharyngeal lymph node metastasis were investigated. The included patients were divided into N1a and N1b groups. Overall survival (OS) and cancer-specific survival (CSS) were assessed using the Kaplan–Meier method and propensity score matching (PSM) analyses. Results This retrospective cohort study examined 759 patients: 70 who were stage N1a and 689 who were stage N1b. Before PSM, N1a group was associated with similar 5-year OS (77.7% vs. 72.4%; P = 0.15) and CSS (85.6% vs. 79.9%; P = 0.09) compared to N1b group. After PSM, a similar OS (75.0% vs. 60.7%; P = 0.12) was found between the radiotherapy and chemoradiotherapy groups. However, N1a group showed a better 5-year CSS (83.8% vs. 71.1%; P = 0.04) compared to N1b group. Stage N1b was an independent risk prognostic factor for CSS (hazard ratio = 2.54, 95% confidence interval: 1.02–6.34; P = 0.04). Conclusions OS was not different between N1a and N1b groups. Retropharyngeal lymph node metastasis defined as stage N1 of the 8th edition American Joint Committee on Cancer staging system is reasonable.

BackgroundThe neuropeptide substance P is a potential biomarker and therapeutic target in cancer. The main objectives of this study were to investigate the expression level of substance P in different breast cancer molecular subtypes and identify its association with clinicopathological parameters of patients and with Ki-67 index.MethodsA retrospective analysis was performed for a total of 164 paraffin-embedded breast cancer tissue samples [42 Her2/neu-enriched, 40 luminal A, 42 luminal B (triple-positive) and 40 triple negative subtypes]. The tissue microarray slides containing specimens were used to determine the expression of substance p and Ki-67 by immunohistochemical staining.ResultsThe mean age of the cohort was 51.35 years. Twenty two percent of cases had low substance P expression levels (TS ≤ 5), while 78% had high expression levels (TS > 5). A significant association was found between SP expression level and breast cancer molecular subtype (p = 0.002), TNM stage (p = 0.034), pN stage (p = 0.013), axillary lymph node metastasis (p = 0.004), ER and PR statuses (pConclusionSP is overexpressed in most of the analyzed tissues and has a negative prognostic value in the breast cancer patients. Besides substance P is a potential therapeutic target in breast cancer.

Lung cancer (LC) is a malignant tumor that poses the greatest threat to human health and life. Most studies suggested that the occurrence of LC is associated with environmental and genetic factors. We aimed to explore the association between COL6A4P2 single nucleotide polymorphisms (SNPs) and CHD risk in the Chinese Southern Han population. Based on the ‘case-control’ experimental design (510 cases and 495 controls), we conducted an association study between five candidate COL6A4P2 SNPs and the corresponding LC risk. Odds ratio (OR) and 95% confidence intervals (CIs) were calculated by logistic regression to analyze the LC susceptibility under different genetic models. The results showed that COL6A4P2 rs34445363 was significantly associated with LC risk under alleles model (OR = 1.26, 95%CI: 1.01–1.58, p = 0.038). In addition, rs34445363 was also significantly associated with LC risk under the log-additive model (OR = 1.26, 95%CI: 1.01–1.58, p = 0.041). The results of subgroup analysis showed that rs34445363 (OR = 1.42, 95%CI: 1.03–1.95, p = 0.033) and rs61733464 (OR = 0.72, 95%CI: 0.52–0.99, p = 0.048) were both significantly associated with LC risk in the log-additive model among participants who were ≤ 61 years old. We also found that the variation of rs34445363 (GA vs. GG, OR = 1.73, 95%CI: 1.04–2.86, p = 0.034) and rs77941834 (TA vs. TT, OR = 1.88, 95%CI: 1.06–3.34, p = 0.032) were associated with LC risk in the codominant model among female participants. Our study is the first to find that COL6A4P2 gene polymorphism is associated with LC risk in the Chinese Han population. Our study provides a basic reference for individualized LC prevention.

Genome alteration signatures reflect recurring patterns caused by distinct endogenous or exogenous mutational events during the evolution of cancer. Signatures of single base substitution (SBS) have been extensively studied in different types of cancer. Copy number alterations are important drivers for the progression of multiple cancer. However, practical tools for studying the signatures of copy number alterations are still lacking. Here, a user-friendly open source bioinformatics tool “sigminer” has been constructed for copy number signature extraction, analysis and visualization. This tool has been applied in prostate cancer (PC), which is particularly driven by complex genome alterations. Five copy number signatures are identified from human PC genome with this tool. The underlying mutational processes for each copy number signature have been illustrated. Sample clustering based on copy number signature exposure reveals considerable heterogeneity of PC, and copy number signatures show improved PC clinical outcome association when compared with SBS signatures. This copy number signature analysis in PC provides distinct insight into the etiology of PC, and potential biomarkers for PC stratification and prognosis., Author summary Genomic DNA alteration signatures are recurring genomic patterns that are the imprints of mutagenic processes accumulated over the lifetime of cancer cell. Copy number alteration is a key driver for the progression of multiple cancer, including prostate cancer, which is particularly driven by complex genome alterations. However, practical tools for studying the signatures of copy number alterations are still lacking. Here a novel bioinformatics tool for copy number signature analysis has been constructed. With this newly developed bioinformatics tool “sigminer”, we performed the first copy number signature analysis in prostate cancer, and an unprecedentedly clear map connecting genome alteration driving factors and prostate cancer clinical outcomes have been illustrated. These analyses provide novel insight into the mutational processes and clinical outcomes of prostate cancer.

The current understanding of clinicopathological features and genomic variants of small-bowel cancer is limited, in part due to the rarity of the disease. However, understanding of these factors is necessary for the development of novel therapeutic agents for small-bowel cancer. Thus, we aimed to identify the clinicopathological features and genomic variants associated with its prognosis and recurrence. We retrospectively examined 24 consecutive patients with primary small-bowel cancer surgically treated between May 2005 and August 2018 and collected 29 tumor specimens. The 29 lesions were subjected to mismatch repair status evaluation, using immunohistochemistry (IHC), and targeted genomic sequencing, after which they were analyzed using a panel of 90 cancer-related genes. IHC revealed that 45% (13/29) of the lesions exhibited deficient mismatch repair. The most common genomic variants in small-bowel cancers were in TP53 (48%, 13/27), followed by KRAS (44%, 12/27), ARID1A (33%, 9/27), PIK3CA (26%, 7/27), APC (26%, 7/27), and SMAD4, NOTCH3, CREBBP, PTCH1, and EP300 (22%, 6/27 each). Overall survival and disease-specific survival of patients with tumor mutational burden (TMB) ≥10 mutations/Mb (n = 17) were significantly better than those of patients with TMB SMAD4 had poorer recurrence-free survival than those with wild-type SMAD4. Our results suggested that TMB and SMAD4 mutations were associated with the prognosis of small-bowel cancer patients. Thus, cancer genomic analysis could be useful in the search for biomarkers of prognosis prediction in small-bowel cancers.

The role of systemic inflammation has not been clearly defined in thyroid cancers. There have been conflicting reports on whether systemic inflammatory markers have predictive value for thyroid cancers. We aimed to evaluate the association between systemic inflammatory markers and clinicopathological factors in thyroid cancers and to assess their predictive value for thyroid cancers in detail. Five hundred thirty-one patients who underwent surgery for thyroid nodules were included. The patient population consisted of 99 individuals (18.6%) with benign thyroid nodules and 432 individuals (81.4%) with thyroid cancers. In 432 patients with thyroid cancers, neutrophil-to-lymphocyte ratio (NLR) was significantly higher in the cases with tumors greater than 2 cm than in those with tumors less than 2 cm. (p = 0.027). NLR and platelet-to-lymphocyte ratio (PLR) were significantly higher in cases with lateral lymph node metastasis (LNM) than in those without LNM (p = 0.007 and 0.090, respectively). The nodule size was significantly higher in benign thyroid nodules than in thyroid cancers (p < 0.001). When the cases were stratified by tumor size, NLR was a significant predictor of thyroid cancers in cases with nodules greater than 2 cm (Exp(B) = 1.85, 95% CI = 1.15–2.97, p = 0.011), but not in those with nodules less than 2 cm. In thyroid cancers, preoperative NLR was associated with pathological prognosticators such as tumor size and lateral lymph node metastasis. When the size difference between thyroid cancers and benign thyroid nodules was adjusted, NLR could be a significant predictor of thyroid cancers.

The first stage of the metastatic cascade often involves motile cells emerging from a primary tumor either as single cells or as clusters. These cells enter the circulation, transit to other parts of the body and finally are responsible for growth of secondary tumors in distant organs. The mode of dissemination is believed to depend on the EMT nature (epithelial, hybrid or mesenchymal) of the cells. Here, we calculate the cluster size distribution of these migrating cells, using a mechanistic computational model, in presence of different degree of EMT-ness of the cells; EMT is treated as given rise to changes in their active motile forces (μ) and cell-medium surface tension (Γ). We find that, for (μ > μmin, Γ > 1), when the cells are hybrid in nature, the mean cluster size, N¯∼Γ2.0/μ2.8, where μmin increases with increase in Γ. For Γ ≤ 0, N¯=1, the cells behave as completely mesenchymal. In presence of spectrum of hybrid states with different degree of EMT-ness (motility) in primary tumor, the cells which are relatively more mesenchymal (higher μ) in nature, form larger clusters, whereas the smaller clusters are relatively more epithelial (lower μ). Moreover, the heterogeneity in μ is comparatively higher for smaller clusters with respect to that for larger clusters. We also observe that more extended cell shapes promote the formation of smaller clusters. Overall, this study establishes a framework which connects the nature and size of migrating clusters disseminating from a primary tumor with the phenotypic composition of the tumor, and can lead to the better understanding of metastasis., Author summary In the process of metastasis, tumor cells disseminate from the primary tumor either as single cells or multicellular clusters. These clusters are potential contributor to the initiation of secondary tumor in distant organs. Our computational model captures the size distribution of migrating clusters depending on the adhesion and motility of the cells (which determine the degree of their EMT nature). Furthermore, we investigate the effect of heterogeneity of cell types in the primary tumor on the resultant heterogeneity of cell types in clusters of different sizes. We believe that the understanding the formation and nature of these clusters, dangerous actors in the deadly aspect of cancer progression, will be useful for improving prognostic methods and eventually better treatments.

The integration of viruses into the human genome is known to be associated with tumorigenesis in many cancers, but the accurate detection of integration breakpoints from short read sequencing data is made difficult by human-viral homologies, viral genome heterogeneity, coverage limitations, and other factors. To address this, we present Exogene, a sensitive and efficient workflow for detecting viral integrations from paired-end next generation sequencing data. Exogene’s read filtering and breakpoint detection strategies yield integration coordinates that are highly concordant with those found in long read validation sets. We demonstrate this concordance across 6 TCGA Hepatocellular carcinoma (HCC) tumor samples, identifying integrations of hepatitis B virus that are validated by long reads. Additionally, we applied Exogene to targeted capture data from 426 previously studied HCC samples, achieving 98.9% concordance with existing methods and identifying 238 high-confidence integrations that were not previously reported. Exogene is applicable to multiple types of paired-end sequence data, including genome, exome, RNA-Seq or targeted capture.

Background: Metaplastic breast cancer (MBC) are rare. The survival outcomes of MBC patients after breast conserving surgery plus radiotherapy (BCS+RT) or mastectomy have not been established. The aim of this study was to compare survival outcomes of MBC patients subjected to BCS+RT or mastectomy therapeutic options.Methods: Patients who were subjected to BCS+RT or mastectomy between 2004 and 2014 were enrolled in this study through the Surveillance, Epidemiology and End Results (SEER) database. Breast cancer-specific survival (BCSS) and the overall survival (OS) of the participants were determined. Cox proportional hazard model and Kaplan Meier method were used to determine the correlation between the two surgical methods and survival outcomes. Results: A total of 1197 patients were enrolled in this study. Among them, 439 patients were subjected to BCS+RT, while 758 patients were subjected to mastectomy. Multivariate analysis showed a significantly high OS for MBC patients who were subjected to BCS+RT compared to those subjected to mastectomy (HR = 0.697, 95% CI = 0.527- 0.922, P=0.012). However, the BCSS for the two groups were statistically comparable (HR = 0.806,95% CI = 0.561-1.158, P= 0.244). After PSM, the BCS+RT and mastectomy groups consisted of 321 patients, respectively. The univariate and multivariate analysis with a 6-month landmark all indicate that patients receiving BCS+RT has higher OS than patients receiving mastectomy (HR = 0.701,95% CI = 0.496-0.990, P=0.044; HR = 0.684,95% CI = 0.479-0.977, P=0.037) while the BCSS was no difference between the two groups(HR = 0.739,95% CI = 0.474-1.153, P = 0.183; HR = 0.741,95% CI = 0.468-1.173, P = 0.200). Conclusion: The BCS+RT therapeutic option exhibits a high OS in MBC patients compared to the mastectomy approach.

Advancements in sequencing have led to the proliferation of multi-omic profiles of human cells under different conditions and perturbations. In addition, many databases have amassed information about pathways and gene “signatures”—patterns of gene expression associated with specific cellular and phenotypic contexts. An important current challenge in systems biology is to leverage such knowledge about gene coordination to maximize the predictive power and generalization of models applied to high-throughput datasets. However, few such integrative approaches exist that also provide interpretable results quantifying the importance of individual genes and pathways to model accuracy. We introduce AKLIMATE, a first kernel-based stacked learner that seamlessly incorporates multi-omics feature data with prior information in the form of pathways for either regression or classification tasks. AKLIMATE uses a novel multiple-kernel learning framework where individual kernels capture the prediction propensities recorded in random forests, each built from a specific pathway gene set that integrates all omics data for its member genes. AKLIMATE has comparable or improved performance relative to state-of-the-art methods on diverse phenotype learning tasks, including predicting microsatellite instability in endometrial and colorectal cancer, survival in breast cancer, and cell line response to gene knockdowns. We show how AKLIMATE is able to connect feature data across data platforms through their common pathways to identify examples of several known and novel contributors of cancer and synthetic lethality., Author summary We describe a new method that incorporates multimodal molecular measurements with gene pathway information for classification and regression prediction tasks. The method combines powerful machine learning methodologies such as ensemble, kernel and stacked learning. A key new contribution is the creation of empirical kernels from pairwise similarities of sample predictions and sample paths along the trees of a random forest specific to a particular gene module. We demonstrate the method performs as well as, or better than, top approaches on three very different cancer genomics applications.

A joint analysis of the NCI60 small molecule screening data, their genetically defective genes, and mechanisms of action (MOA) of FDA approved cancer drugs screened in the NCI60 is proposed for identifying links between chemosensitivity, genomic defects and MOA. Self-Organizing-Maps (SOMs) are used to organize the chemosensitivity data. Student’s t-tests are used to identify SOM clusters with enhanced chemosensitivity for tumor cell lines with versus without genetically defective genes. Fisher’s exact and chi-square tests are used to reveal instances where defective gene to chemosensitivity associations have enriched MOAs. The results of this analysis find a relatively small set of defective genes, inclusive ofABL1,AXL,BRAF,CDC25A,CDKN2A,IGF1R,KRAS,MECOM,MMP1,MYC,NOTCH1,NRAS,PIK3CG,PTK2,RPTOR,SPTBN1,STAT2,TNKSandZHX2, as possible candidates for roles in chemosensitivity for compound MOAs that target primarily, but not exclusively, kinases, nucleic acid synthesis, protein synthesis, apoptosis and tubulin. These results find exploitable instances of enhanced chemosensitivity of compound MOA’s for selected defective genes. Collectively these findings will advance the interpretation of pre-clinical screening data as well as contribute towards the goals of cancer drug discovery, development decision making, and explanation of drug mechanisms.

Background Osteoporosis has increased and developed into a serious public health concern worldwide. Despite the high prevalence, osteoporosis is silent before major fragility fracture and the osteoporosis screening rate is low. Abdomen-pelvic CT (APCT) is one of the most widely conducted medical tests. Artificial intelligence and radiomics analysis have recently been spotlighted. This is the first study to evaluate the prediction performance of femoral osteoporosis using machine-learning analysis with radiomics features and APCT. Materials and methods 500 patients (M: F = 70:430; mean age, 66.5 ± 11.8yrs; range, 50–96 years) underwent both dual-energy X-ray absorptiometry and APCT within 1 month. The volume of interest of the left proximal femur was extracted and 41 radiomics features were calculated using 3D volume of interest analysis. Top 10 importance radiomic features were selected by the intraclass correlation coefficient and random forest feature selection. Study cohort was randomly divided into 70% of the samples as the training cohort and the remaining 30% of the sample as the validation cohort. Prediction performance of machine-learning analysis was calculated using diagnostic test and comparison of area under the curve (AUC) of receiver operating characteristic curve analysis was performed between training and validation cohorts. Results The osteoporosis prevalence of this study cohort was 20.8%. The prediction performance of the machine-learning analysis to diagnose osteoporosis in the training and validation cohorts were as follows; accuracy, 92.9% vs. 92.7%; sensitivity, 86.6% vs. 80.0%; specificity, 94.5% vs. 95.8%; positive predictive value, 78.4% vs. 82.8%; and negative predictive value, 96.7% vs. 95.0%. The AUC to predict osteoporosis in the training and validation cohorts were 95.9% [95% confidence interval (CI), 93.7%-98.1%] and 96.0% [95% CI, 93.2%-98.8%], respectively, without significant differences (P = 0.962). Conclusion Prediction performance of femoral osteoporosis using machine-learning analysis with radiomics features and APCT showed high validity with more than 93% accuracy, specificity, and negative predictive value.

Background The current standard of care (SOC) for whole breast radiotherapy (WBRT) in the US is conventional tangential photon fields. Advanced WBRT techniques may provide similar tumor control and better normal tissue sparing, but it is controversial whether the medical benefits of an advanced technology are significant enough to justify its higher cost. Objective To analyze the cost-effectiveness of six advanced WBRT techniques compared with SOC. Methods We developed a Markov model to simulate health states for one cohort of women (65-year-old) with early-stage breast cancer over 15 years after WBRT. The cost effectiveness analyses of field-in-field (FIF), hybrid intensity modulated radiotherapy (IMRT), full IMRT, standard volumetric modulated arc therapy (STD-VMAT), multiple arc VMAT (MA-VMAT), non-coplanar VMAT (NC-VMAT) compared with SOC were performed with both tumor control and radiogenic side effects considered. Transition probabilities and utilities for each health state were obtained from literature. Costs incurred by payers were adopted from literature and Medicare data. Quality-adjusted life years (QALYs) and incremental cost-effectiveness ratio (ICER) were calculated. One-way sensitivity analyses and probabilistic sensitivity analyses (PSA) were performed to evaluate the impact of uncertainties on the final results. Results FIF has the lowest ICER value of 1,511 $/QALY. The one-way analyses show that the cost-effectiveness of advanced WBRT techniques is most sensitive to the probability of developing contralateral breast cancer. PSAs show that SOC is more cost effective than almost all advanced WBRT techniques at a willingness-to-pay (WTP) threshold of 50,000 $/QALY, while FIF, hybrid IMRT and MA-VMAT are more cost-effective than SOC with a probability of 59.2%, 72.3% and 72.6% at a WTP threshold of 100,000 $/QALY, respectively. Conclusions FIF might be the most cost-effective option for WBRT patients at a WTP threshold of 50,000 $/QALY, while hybrid IMRT and MA-VMAT might be the most cost-effective options at a WTP threshold of 100,000 $/QALY.

IntroductionBefore anti-EGFR therapy is given to patients with colorectal cancer, it is required to determineKRASmutation status in tumor. When tumor tissue is not available, cell-free DNA (liquid biopsy) is commonly used as an alternative. Due to the low abundance of tumor-derived DNA in cell-free DNA samples, methods with high sensitivity were preferred, including digital polymerase chain reaction, amplification refractory mutation system and next-generation sequencing. The aim of this systemic review and meta-analysis was to investigate the accuracy of those methods in detectingKRASmutation in cell-free DNA sample from patients with colorectal cancer.MethodsLiterature search was performed in Pubmed, Embase, and Cochrane Library. After removing duplicates from the 170 publications found by literature search, eligible studies were identified using pre-defined criteria. Quality of the publications and relevant data were assessed and extracted thereafter. Meta-DiSc and STATA softwares were used to pool the accuracy parameters from the extracted data.ResultsA total of 33 eligible studies were identified for this systemic review and meta-analysis. After pooling, the overall sensitivity, specificity, and diagnostic odds ratio were 0.77 (95%CI: 0.74–0.79), 0.87 (95%CI: 0.85–0.89), and 23.96 (95%CI: 13.72–41.84), respectively. The overall positive and negative likelihood ratios were 5.55 (95%CI: 3.76–8.19) and 0.29 (95%CI: 0.21–0.38), respectively. Area under curve of the summarized ROC curve was 0.8992.ConclusionDigital polymerase chain reaction, amplification refractory mutation system, and next-generation sequencing had overall high accuracy in detectingKRASmutation in cell-free DNA sample. Large prospective randomized clinical trials are needed to further convince the accuracy and usefulness ofKRASmutation detection using cfDNA/liquid biopsy samples in clinical practice.Trial registrationPROSPERO CRD42020176682;https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=176682.

Cancer occurs via an accumulation of somatic genomic alterations in a process of clonal evolution. There has been intensive study of potential causal mutations driving cancer development and progression. However, much recent evidence suggests that tumor evolution is normally driven by a variety of mechanisms of somatic hypermutability, which act in different combinations or degrees in different cancers. These variations in mutability phenotypes are predictive of progression outcomes independent of the specific mutations they have produced to date. Here we explore the question of how and to what degree these differences in mutational phenotypes act in a cancer to predict its future progression. We develop a computational paradigm using evolutionary tree inference (tumor phylogeny) algorithms to derive features quantifying single-tumor mutational phenotypes, followed by a machine learning framework to identify key features predictive of progression. Analyses of breast invasive carcinoma and lung carcinoma demonstrate that a large fraction of the risk of future clinical outcomes of cancer progression—overall survival and disease-free survival—can be explained solely from mutational phenotype features derived from the phylogenetic analysis. We further show that mutational phenotypes have additional predictive power even after accounting for traditional clinical and driver gene-centric genomic predictors of progression. These results confirm the importance of mutational phenotypes in contributing to cancer progression risk and suggest strategies for enhancing the predictive power of conventional clinical data or driver-centric biomarkers., Author summary Cancer results from mutations in previously healthy cell populations that typically accumulate over a period of years before tumor growth is apparent. This process is governed by the laws of evolution, by which random mutations arising in cells will occasionally lead to selection for particular cell populations with growth advantages. How this process unfolds in any given tumor is highly random and idiosyncratic, however, making tumor growth difficult to predict. One reason tumor evolution is so random is that tumors frequently contain mutations that bias the cancer cells to generate new mutations in different ways, yet variations among these mechanisms of mutability (which we call “mutational phenotypes”) themselves provide predictive power for a cancer’s future progression. However, little is known about the degree to which the risk of cancer progressing is characterized by these variations in mutation mechanism as opposed to other sources. In this work, we examine the question of how much of the risk of cancer progression is explained by these differences patient-to-patient in mutability preferences. We find that approximately a third of the risk of future cancer progression is accounted for by variations in mutational phenotypes. Furthermore, these mutational phenotypes are complementary to and only partially redundant with other sources of predictive information, a finding confirmed by showing that machine learning models using such information can enhance our ability to predict which cancers progress and recur beyond what can be accomplished from more traditional genomic and clinical data sources alone.

Objective The aim of this study was to investigate the usefulness of staging chest-CT in terms of diagnostic yield and false-referral rate in patients with operable breast cancer. Materials and methods This study was approved by the institutional review border. In this retrospective study, we reviewed patients who underwent staging chest-CT between January 2014 and June 2016. Reference standard was defined as a combination of pathology and radiologic tumor changes in accordance with primary tumor or metastatic lesions and stability during the 12-month follow-up period. We calculated diagnostic yield and false-referral rates stratified by pathologic stage. The important ancillary findings of staging chest-CT were also recorded. Results A total of 1,342 patients were included in this study. Of these, four patients (0.3%; 4/1342) had true pulmonary metastasis. Diagnostic yields of stage I, II, III disease were 0.0% (0/521), 0.3% (2/693), and 1.6% (2/128), respectively. The overall false-referral rate was 4.6% (62/1342); false-referral rates of stage I, II, and III disease were 5.0% (26/521), 3.8% (26/693), and 7.8% (10/128), respectively. No occult thoracic metastasis occurred within 12 months of staging chest-CT. Nineteen patients showed significant ancillary findings besides lung metastasis, including primary lung cancer (n = 9). The overall diagnostic yield of ancillary findings was 1.7% (23 of 1342). Conclusions The incidence of pulmonary metastasis was near zero for pathologic stages I/II and slightly higher (although still low; 1.6%). for stage III. Considering its low diagnostic yield and substantial false-referral rates, staging chest-CT might not be useful in patients with operable breast cancer.

Background Integrating additional factors into the TNM staging system is needed for more accurate risk classification and survival prediction for patients with cutaneous melanoma. In the present study, we introduce machine learning as a novel tool that incorporates additional prognostic factors to improve the current TNM staging system. Methods and findings Cancer-specific survival data for cutaneous melanoma with at least a 5 years follow-up were extracted from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute and split into the training set (40,781 cases) and validation set (5,390 cases). Five factors were studied: the primary tumor (T), regional lymph nodes (N), distant metastasis (M), age (A), and sex (S). The Ensemble Algorithm for Clustering Cancer Data (EACCD) was applied to the training set to generate prognostic groups. Utilizing only T, N, and M, a basic prognostic system was built where patients were stratified into 10 prognostic groups with well-separated survival curves, similar to 10 AJCC stages. These 10 groups had a significantly higher accuracy in survival prediction than 10 stages (C-index = 0.7682 vs 0.7643; increase in C-index = 0.0039, 95% CI = (0.0032, 0.0047); p-value = 7.2×10−23). Nevertheless, a positive association remained between the EACCD grouping and the AJCC staging (Spearman’s rank correlation coefficient = 0.8316; p-value = 4.5×10−13). With additional information from A and S, a more advanced prognostic system was established using the training data that stratified patients into 10 groups and further improved the prediction accuracy (C-index = 0.7865 vs 0.7643; increase in C-index = 0.0222, 95% CI = (0.0191, 0.0254); p-value = 8.8×10−43). Both internal validation using the training set and temporal validation using the validation set showed good stratification and a high predictive accuracy of the prognostic systems. Conclusions The EACCD allows additional factors to be integrated into the TNM to create a prognostic system that improves patient stratification and survival prediction for cutaneous melanoma. This integration separates favorable from unfavorable clinical outcomes for patients and improves both cohort selection for clinical trials and treatment management.

BackgroundYes-associated protein 1 (YAP1) is a key effector molecule regulated by the Hippo pathway and described as a poor prognostic factor in breast cancer. Tumor protein 53 (TP53) mutation is well known as a biomarker related to poor survival outcomes. So far clinical characteristics and survival outcome according to YAP1 and TP53 mutation have been poorly identified in breast cancer.Patients and methodsRetrospectively, 533 breast tumor tissues were collected at the Seoul St Mary’s hospital and Gangnam Severance Hospital from 1992 to 2017. Immunohistochemistry with YAP1 and p53 specific antibodies were performed, and the clinical data were analyzed.ResultsMutant p53 pattern was associated with aggressive tumor features and advanced anatomical stage. Inferior overall survival (OS) and recurrence free survival (RFS) were related with mutant p53 pattern cases with low nuclear YAP1 expression (P= 0.0009 andP= 0.0011, respectively). Multivariate analysis showed that mutant p53 pattern was an independent prognostic marker for OS [hazard ratios (HR): 2.938, 95% confidence intervals (CIs): 1.028–8.395, P = 0.044] and RFS (HR: 1.842, 95% CIs: 1.026–3.304). However, in cases with high nuclear YAP1 expression, there were no significantly difference in OS and RFS according to p53 staining pattern.ConclusionWe found that mutant p53 pattern is a poor prognostic biomarker in breast tumor with low nuclear YAP1 expression. Our findings suggest that interaction between nuclear YAP1 and p53 expression pattern impact survival outcomes.

Background Gastric cancer (GC) patients frequently develop peritoneal metastasis. Recently, it has been reported that peritoneal mesothelial cells (PMCs) activated by GC cells acquire a migratory capacity and promote GC cell invasion. The invasiveness of PMCs reportedly depends on the activity of Tks5, an adaptor protein required for invadopodia formation. However, the relationship between clinicopathologic features and Tks5 expression in PMCs has been poorly documented. In this study, we evaluated the clinicopathologic significance of the Tks5 expression of PMCs in GC patients. Materials and methods A total of 110 GC patients who underwent gastrectomy were enrolled in this study. Tks5 expressions in PMCs from the greater omentum, lesser omentum and retroperitoneum were evaluated by immunohistochemistry. We analyzed the correlation between Tks5 expressions in PMCs and the patients’ clinicopathologic features. Results Tks5 expression was found in 71 (64.5%) of the 110 patients, while 39 (35.5%) were Tks5-negative. Tks5 positivity was significantly (p = 0.038) associated with a greater tumor depth (i.e., T3/4 compared with T1/T2). Peritoneal recurrence was found in 12 of 98 cases within 3 years of surgery. The 3-year peritoneal recurrence-free survival (PRFS) rate in Tks5-positive cases was significantly poorer than that in Tks5-negative cases (80.1% vs 97.4%, p = 0.024). Multivariate analysis revealed that Tks5 positivity and lymph node metastasis were independent factors for PRFS. Conclusion Tks5 is frequently expressed in PMCs in advanced-stage gastric cancer. Tks5 might be a useful predictor for peritoneal recurrence in GC patients.

Timely and accurate identification of molecular alterations in solid tumors is essential for proper management of patients with advanced cancers. This has created a need for rapid, scalable comprehensive genomic profiling (CGP) systems that detect an increasing number of therapeutically-relevant variant types and molecular signatures. In this study, we assessed the analytical performance of the TruSight Oncology 500 High-Throughput assay for detection of somatic alterations from formalin-fixed paraffin-embedded tissue specimens. In parallel, we developed supporting software and automated sample preparation systems designed to process up to 70 clinical samples in a single NovaSeq 6000TM sequencing run with a turnaround time of 99% overall accuracy and precision. Our results demonstrate that the high-throughput CGP assay is a reliable method for accurate detection of molecular alterations in support of precision therapeutics in oncology. The supporting systems and scalable workflow allow for efficient interpretation and prompt reporting of hundreds of patient cancer genomes per week with excellent analytical performance.

Background Small-cell lung cancer (SCLC) is an aggressive disease with high metastatic potential and poor prognosis. Due to its low prevalence, epidemiological and clinical information of SCLC patients retrieved from lung cancer registries is scarce. Patients and methods This was an observational multicenter study that enrolled patients with lung cancer and thoracic tumors, recruited from August 2016 to January 2020 at 50 Spanish hospitals. Demographic and clinical data, treatment patterns and survival of SCLC patients included in the Thoracic Tumor Registry (TTR) were analyzed. Results With a total of 956 cases, the age of 64.7 ± 9.1 years, 78.6% were men, 60.6% smokers, and ECOG PS 0, 1 or ≥ 2 in 23.1%, 53.0% and 23.8% of cases, respectively. Twenty percent of patients had brain metastases at the diagnosis. First-line chemotherapy (CT), mainly carboplatin or cisplatin plus etoposide was administered to >90% of patients. In total, 36.0% and 13.8% of patients received a second and third line of CT, respectively. Median overall survival was 9.5 months (95% CI 8.8–10.2 months), with an estimated rate of 70.3% (95% CI 67.2–73.4%), 38.9% (95% CI 35.4–42.4%), and 14.8% (95% CI 11.8–17.8%) at 6, 12 and 24 months respectively. Median progression-free survival was 6.3 months. Higher mortality and progression rates were significantly associated with male sex, older age, smoking habit, and ECOG PS 1–2. Long-term survival (> 2 years) was confirmed in 6.6% of patients, showing a positive correlation with better ECOG PS, poor smoking and absence of certain metastases at diagnosis. Conclusion This study provides an updated overview of the clinical situation and treatment landscape of ES-SCLC in Spain. Our results might assist oncologists to improve current clinical practice towards a better prognosis for these patients.

Background In many malignancies including intrahepatic cholangiocarcinoma (iCCA), prognostic significance of host-related inflammatory / immunonutritional markers have attracted a lot of attention. However, it is unclear which is the strongest prognostic indicator for iCCA among these markers. The aim of this study was to firstly evaluate the prognostic utility of inflammatory / immunonutritional markers in resected iCCA patients using a multiple comparison in addition to a new marker, lymphocyte-to-C-reactive protein (CRP) score. Methods A total of sixty iCCA patients, who underwent surgical resection between October 2004 and April 2019, were enrolled in this study. Their clinical and pathological data were retrospectively assessed using univariate and multivariate analysis to determine prognostic predictors for disease specific survival (DSS). Moreover, these patients, who were divided into high and low groups based on lymphocyte-to-CRP score, were compared these survival outcomes using Kaplan-Meier analysis with a log-rank test. Results In multivariate analysis, the significant prognostic factors were preoperative lymphocyte-to-CRP score (p = 0.008), preoperative CRP-to-albumin ratio (CAR; p = 0.017), pathological T category (p = 0.003), and pathological vascular invasion (p < 0.001). Resected iCCA patients with a low lymphocyte-to-CRP score (score 0) had significant better prognosis than patients with a high score (score 1 or 2) (p = 0.016). Notably, the mortality of the high lymphocyte-to-CRP score group did not show statistically difference from the poor mortality of unresected iCCA patients (p = 0.204). Conclusions Preoperative lymphocyte-to-CRP score was the strongest prognostic indicator in iCCA patients with surgical resection. In these patients, early intervention with nutritional support should be considered prior to operation.

Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. There is an urgent need to identify prognostic markers for patients undergoing curative resection of CRC. The detection of circulating tumor cells in peripheral blood is a promising approach to identify high-risk patients with disseminated disease in colorectal cancer. This study aims to evaluate the prognostic relevance of preoperative CTCs using the Cellsearch® system (CS) in patients, who underwent resection with curative intent of different stages (UICC I-IV) of colorectal cancer. Out of 91 Patients who underwent colorectal resection, 68 patients were included in this study. CTC analysis was performed in patients with CRC UICC stages I-IV immediately before surgery. Data were correlated with clinicopathological parameters and patient outcomes. One or more CTCs/7.5 mL were detected in 45.6% (31/68) of patients. CTCs were detected in all stages of the Union of International Cancer Control (UICC), in stage I (1/4, 25%), in stage II (4/12, 33.3%), in stage III (5/19, 26.3%) and in stage IV (21/33, 63.6%). The detection of ≥ 1 CTCs/ 7.5ml correlated to the presence of distant overt metastases (p = 0.014) as well as with shorter progression-free (p = 0.008) and overall survival (p = 0.008). Multivariate analyses showed that the detection of ≥ 1 CTCs/ 7.5ml is an independent prognostic indicator for overall survival (HR, 3.14; 95% CI, 1.18–8.32; p = 0.021). The detection of CTCs is an independent and strong prognostic factor in CRC, which might improve the identification of high-risk patients in future clinical trials.

Background Utility of the sentinel lymph node (SLN) biopsy in some malignancies has been reported, however, research on that of gallbladder cancer (GBC) is rare. The aim of this study is to investigate whether the concept of SLN is applicable to T2/3 GBC. Methods A total of 80 patients who underwent resection for gallbladder cancer were enrolled in this study. Patients with GBC were stratified into two groups based on the location of tumor, peritoneal-side (T2p or 3p) and hepatic-side (T2h or 3h) groups. We evaluated the relationship between cystic duct node (CDN) and downstream lymph node (LN) status. CDN was defined as a SLN in this study. Results Thirty-eight patients were classified into T2, including T2p (n = 18) and T2h (n = 20), and 42 patients into T3, including T3p (n = 22) andT3h (n = 20). The incidence of LN metastasis was significantly higher in hepatic-side than peritoneal-side in both T2 and T3 (P = 0.036 and 0.009, respectively). In T2, 14 T2p had negative CDN and downstream LN, however, three T2h had negative CDN and positive downstream LNs (defined as a skipped LN metastasis) (P = 0.043). In T3, patients with skipped LN metastasis were significantly higher in T3h (n = 11) than those in T3p (n = 2) (P Conclusion The concept of SLN can be applicable to T2p GBC, where the downstream LNs dissection can be omitted.